Research

The central theme of our research is medical population genetics. We are interested in computational and statistical methods for understanding the genetic architecture of common diseases. On-going projects include:

With rapidly decreasing costs, sequencing is emerging as appealing alternative to genotyping arrays for large scale disease studies. We are interested in the design and analysis of cost-effective sequencing-based studies over tens of thousands of samples with the goal of maximizing power to identify disease associations per budget invested. See our extremely low-coverage sequencing GWAS paper (10.1038/ng.2283) or Mancuso et al Nat Genetics 2015.

Disease studies in admixed populations.

The genome of admixed individuals, such as African Americans or Latinos, is a mosaic of chromosomal regions originating from the ancestral populations. Inferring the ancestral origin of each of these regions is a key component in disease mapping in admixed populations. Our ongoing research focuses on a wide array of problems in this area ranging from methods for local ancestry inference to optimally powered association statistics that take into account differences in the genetic makeup of the ancestral populations. See, our LAMP-LD (10.1093/bioinformatics/bts144) method for local ancestry inference as well as our MIXSCORE approach for incorporation of admixture and GWAS association signal to improve power (10.1371/journal.pgen.1001371).